Maternal immune activation during pregnancy is associated with worst socio-adaptive behaviors in autism spectrum disorders

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Maternal immune activation (MIA) during the mid-pregnancy is a known risk factor for ASD. Although reported in 15% of affected individuals, little is known about the specificity of their clinical profiles. Adaptive skills represent a holistic approach to a person's competencies and reflect specifically in autism, their strengths and difficulties. Methods In this study, we hypothesised that individual with ASD with a history of MIA (MIA + ) could be more severely socio-adaptively impaired than those without MIA during pregnancy (MIA − ). To answer this question, we considered two independent cohorts of individuals with ASD (PARIS study and FACE ASD) screened for pregnancy history, and used a supervised and unsupervised statistical approach. Results We included 295 mother-child dyads with 14% of them with MIA + . We found that ASD-MIA + individuals displayed more severe maladaptive behaviors, specifically in their socialization abilities. MIA + directly influenced individual's socio-adaptive skills, independent of other covariates, including ASD severity. Interestingly, MIA + may affected persistently the socio-adaptive behavioral trajectories of individuals with ASD. Limitations : The current study has a retrospective design with possible recall bias regarding the MIA event and, even if pooled from two cohorts, has a relatively small population. In addition, we were limited by the number of covariables available potentially impacted socio-adaptive behaviors. Larger prospective study with additional dimensions related to ASD is needed to confirm our results Conclusions Specific pathophysiological pathways may explain these clinical peculiarities of ASD- MIA + individuals, and may open the way to new perspectives in deciphering the phenotypic complexity of autism and for the development of specific immunomodulatory strategies. Neuroimmunology Autoimmune diseases Inflammation Machine Learning Figures Figure 1 Figure 2 Background Autism spectrum disorders (ASD) are heterogeneous childhood-onset neurodevelopmental disorders characterised by social communication impairment or interaction and repetitive or stereotyped behaviours. Its incidence is 1 in 50 to 1 in 100 birth, affecting 52 million people worldwide [ 1 ]. The etiopathogenesis of ASD results from the close intertwining of genetic predispositions and environmental risk factors. Among the known environmental insults, maternal immune activation during the mid-pregnancy (MIA) - either due to maternal autoimmune diseases or to infections - is associated with an increased risk of ASD in the offspring [ 2 ]. In accordance with epidemiological evidences, well replicated pre clinical studies show that this association is mediated by a direct action of maternal immune mediators ( i.e. cytokines) on fetal cortical neurons, disrupting normal neurodevelopment and leading to autism-like behaviours in the pups [ 3 ]. Years of intensive research have made it possible to divide the common and heterogeneous autism spectrum into rarer but etiopathogenically homogeneous entities, based mainly on common genetic variants [ 4 ]. This approach allows to identify and better understand common pathophysiological pathways and thus the emergence of potential targeted therapies. Nonetheless, few studies have attempted to characterise ASD subgroup according to common pathogenic environmental factors. Despite a history of MIA being frequent, approximatively reported in 15% of ASD individuals, there is surprisingly little data on their specific clinical profiles. Clinical studies often use symptom scales to assess the clinical characteristics of individuals and the severity of the disorder, which do not reflect their adaptability to the environment. According to the American Association on Intellectual and Developmental Disorders (AAIDD), adaptive behaviour is «the collection of conceptual, social, and practical skills that all people learn in order to function in their daily lives» [ 5 ]. Adaptive skills thus represent a higher concept of functionning, taking into account all dimensions of a person in his/her environment [ 6 ]. The level of autonomy and adaptation of children with neurodevelopmental disorders is frequently assessed with the second edition of the Vineland Adaptive Behavior Scale (VABS) [ 6 ] [ 7 ] which measures adaptive behaviors from three main areas: communication, daily living skills and socialization.. As an exploratory study, we decided to use the VABS to explore the impact of MIA on the phenotype of individuals with ASD. We hypothesised that MIA + individuals would display more severe socio-maladaptive behaviors than MIA − ASD. To perform this study, we considered two independent cohorts of individuals with ASD (PARIS study and FACE ASD) screened for pregnancy history, and used a supervised and unsupervised statistical algorithms to decipher the interactions between MIA and adaptive behaviors in autism. Methods Participants We included in our study children with ASD enrolled in the PARIS study, conducted by the Excellence Centre for Autism & Neuro-developmental Disorders (InovAND - Robert Debré Hospital, Paris, France) between March 2017 to April 2021. This study was approved by the local ethics committee (2021-27 N° IDRCB: 2021-A00489-32). We also enrolled ASD individuals from an independent sample from eight Expert Centers for ASD (Créteil, Bordeaux, Grenoble, Versailles, Marseille, Caen, Strasbourg, Lyon) coordinated by Fondation FondaMental. The relevant Ethical Review Board (CPP- Est IV) approved the appraisal protocol on 18 June 2019. All participants gave their informed consent. Considering the frequency of the MIA event (12–15%) and the number of individual per sample, we pooled all individuals to increase the power analysis of the study. The diagnosis of ASD was performed according to DSM-5 criteria [ 8 ] by summing up the information from the Autism Diagnostic Interview-Revised [ 9 ], the Autism Diagnostic Observation Schedule − 2nd edition (ADOS-2) [ 10 ] and clinical records of individuals. All participants were screened with a parental semi-structured interview for pre- and peri- natal history. We focused on any history of MIA during pregnancy. Based on this information, children were then split either into MIA (MIA + ) or in non-MIA (MIA - ) sub-groups. We considered mothers with a significant history of an MIA-related event when they were: (i) with an autoimmune disease as listed by the American Autoimmune Related Diseases Association [ 11 ] and (ii) with a viral or bacterial infection during pregnancy with a fever over 38.5°C for more than 24 hours. Mothers with an infection resulting from a pathogen with a well-documented direct brain cytopathic effect (such as cytomegalovirus infection) were excluded. Statistical analysis Before each analysis, the normality of the distribution of the variables was tested with a Shapiro-Wilk test. For continuous variables Student’s t-tests or Wilcoxon tests were used accordingly. For categorical variables, the Fisher test was used. Only linear models with a normal distribution of residuals were used. In order to test the predictions, we performed a hierarchical regression analysis. Hierarchical regression is a type of regression model in which predictors are added to or removed from the regression model in steps and/or blocks of variables. It allows for the analysis of the variance explained in a dependent variable by more than one predictor variable. Hierarchical regression analysis are in supplementary materials . The final models of multivariate analysis (also found in supplementary materials) were all adjusted on sex and ASD scales (SRS T-score / ADOS total score). Unsupervised classification trees were generated using R package “Party” [ 12 ]. The relevance of the groups identified by the classification trees were then tested using ANOVA with post-hoc Tukey for multiple comparisons of means. Then, we performed supervised classification methods using the R package “mlr3''.[ 13 ] In sum, we split the sample in 2 groups, 80% of the individuals for training and the remaining for validation. As the MIA + individuals were under-represented, we used an oversampling method with a 3.5 ratio. The sample characteristics before and after oversampling are in Supplementary Fig. 1. For classification, we used both a logistic regression classification learner and a linear discriminant analysis classification learner. The learning parameters used by the model were then evaluated using the package R package «iml» [ 14 ] with three components: feature effects, Shapley values and feature importance. Lastly, to better understand the direct and indirect effects within this model, we used path analysis with R package «lavaan» [ 15 ]. Statistical analysis was performed using R studio version 4.2.1. Results General characteristics We finally considered 295 mother-child dyads in our study, with a history of MIA reported in 14% of mothers (n = 40) (MIA + ). Dyads without a history of MIA (n = 255, 86%) were used as a comparison group (MIA − ). The prenatal history and birth parameters are provided in Table 1 . MIA – n = 255 (86%) MIA + n = 40 (14%) p-value Table 1 Prenatal and birth parameters of the population studies. MIA: Maternal immune activation Prenatal Yes / No (%) Fisher test Threatened preterm delivery (TPD) 15/240 (6/94) 4/39 (10/90) 0,3 High blood pressure (HBP) 8/247 (3/97) 2/38 (5/95) 0,6 Placenta Praevia 2/253 (0,8/98,2) 2/38 (5/95) 0,9 Premature rupture of membranes (PROM) 0/255 (0/255) 3/37 (7,5/92,5) 0,002 Materno-foetal infection (MFI) 2/253 (0,8/98,2) 3/37 (7,5/92,5) 0,02 Sex ratio M/F 211/43 (83/17) 35/4 (90/10) 0,35 Birth parameters median (IQR) Wilcox test Height(cm) 50 (3) 50 (4) 0,25 Weight (g) 3370 (1015) 3420 (545) 0,96 Head Circumference (cm) 35 (1,5) 35 (3) 0,19 APGAR 1 minute 10 (0) 10 (1) 0,052 APGAR 5 minutes 10 (0) 10(0) 0,08 We observed that mothers with MIA during pregnancy had more history of premature rupture of membranes (PROM) (p-value = 0.002) and maternofetal infection (MFI) (p-value = 0.02) than those without MIA. ASD-MIA + individuals did not differ from those without a history of MIA in term of symptoms severity estimated with the SRS T-score (p-value = 0.6) or ADOS total score (p-value = 0.4). Univariate analysis did not reveal any difference in any of the three sub-domain of the VABS: communication (p-value = 0.3), ssocialisation (p-value = 0.2), daily living skills (DLS) (p-value = 0.4) domains (Table 2 ). MIA – N = 255 (86%) MIA + N = 40 (14%) p-value Table 2 Autistic severity profile of the population studies. MIA: Maternal immune activation, SRS: Social Responsiveness Scale 2nd edition; ADOS Autism Diagnostic Observation Schedule 2nd edition; VABS: Vineland adaptative behavior scale second edition median (IQR) Wilcox test SRS (T-score) 73 (16) 76 (16,5) 0,6 ADOS (total score) 18 (8) 16 (10) 0,4 VABS – Communication subdomain score 67 (36) 64 (38) 0,3 VABS - Socialisation subdomain score 64 (35) 57 (36) 0,2 VABS - Daily Living Skills subdomain score 69 (25) 66 (19) 0,4 More severe impact on adaptative behaviors related to socialization is associated with MIA during pregnancy Previous studies found a more severe social impairement in MIA + children [ 16 ]. We found, that SRS T-score and ADOS total score were correlated with the three sub-scores of VABS (Fig. 1 A). Accordingly, in adjusted analysis, we observed that more severe socio-maladaptive behaviors in ASD individuals was associated with a MIA during pregnancy (p-value = 0.006) (Details of the hierarchical regression analysis are in supplementary Table 1 and Table 2 ). To confirm this association, we used a non-supervised classification tree isolating three groups of individuals (Fig. 1 B): (i) A MIA low-probability group (VABS - Socialisation > 55 and ADOS total score > 15) with 1% of MIA + ; (ii) a medium-probability group (VABS - Socialisation > 55 and ADOS total score = < 15) with 11% of MIA + ; and (iii) a high-probability group (VABS - Socialisation = < 55) with 17% of MIA + . Significant differences between the high-probability group and the low-probability group were observed (p-value = 0.002). Finally, we further validated our results by applying a supervised classification algorithm with two distinct predictive models. Applying logistic regression classification, we discriminated MIA + individuals with an accuracy of 70%, a sensitivity of 84%, a specificity of 27% and an area under the curve (AUC) of 72%. In accordance with our initial hypothesis, the most robust parameter to classify children was the VABS - Socialisation score followed by ADOS total score (Fig. 1 C and Supplementary Fig. 2A and 2B ). Linear discriminant analysis classification (LDA) reported similar results with an accuracy of 72%, a sensitivity of 84%, a specificity of 33% and AUC of 66%. Of note, the VABS - Socialisation score was also the most important parameter allowing classification, but in LDA, both ADOS total score and SRS T-score were pertinent to classify children (Fig. 1 D). Considering the communication domain, we observed that more severe score was also associated with a history of MIA (p-value = 0.045) (details of the multiple linear regression results in supplementary Table 3 ). We next used a non-supervised classification tree also isolating three groups of individuals (Fig. 1 E): (i) A MIA low-probability group (VABS - communication > 66) with 10% of MIA + ; (ii) a medium-probability group (VABS – Communication = 19 ) with 12% of MIA + ; and (iii) a high-probability group (VABS - Communication = < 66 and ADOS total score < 19)) with 18% of MIA + . No significant differences was found between groups (p-value < 0.08). Thus, we considered that the communication domain of the VABS was not associated with MIA. Lastly, no association was observed between DLS and MIA (p-value = 0.2) ( supplementary Table 4 ). In sum, we found that, in ASD children, more severe adaptive behaviours in socialisation were associated with a higher probability of a history of MIA during pregnancy. MIA may directly affected the socio-maladaptive behaviors in autism We observed that MIA was associated with more pregnancy complications also known to increase independently the risk for ASD (Table 1 ) [ 17 ]. Pregnancy complications and more severe ASD symptomatology were correlated with more adaptive behaviours later on ( Supplementary Fig. 3 ). Adjusting for these potential factors and corroborating our previous results, we investigated whether a history of MIA was associated with poorer adaptive behavior and if so, the mediator of this association. Using adjustment models, we found no any association between the history of MIA and communication (p-value = 0.15) or DLS (p-value = 0.63) sub-domain but a significant association with poorer socio-adaptive behaviours (p-value = 0.03) ( supplementary Tables 5, 6 and 7 ). Unsupervised analysis with a linear model regression learner confirmed this association (mean absolute error = 20.2; mean qquare error = 562.7; root mean square error = 23.7, R-square = 0.16) (Fig. 2 A). According to feature importance, MIA appeared to predict the intensity of communication deficit, just after the intensity of the global autistic symptom severity itself (Fig. 2 B and Supplementary Fig. 4). Finally, we explored whether there was a causal link between the MIA and the impairment intensity of socio-adaptive skills. We used structural equation modelling and applied a path analysis to our dataset. We found, with a good model performance (Fig. 2 C), that MIA influenced directly the socio-adaptive skills of children, independently of pregnancy complications or global severity of autism symptoms (Fig. 2 D). Discussion Using multiple and complementary statistical approaches, we found that ASD individuals with a history of MIA during pregnancy displayed poorer socio-adaptive skills. For individual with a VABS socialization subdomain score 55. Social-adaptive skills are a central node of autism symptomatology. Compared to healthy children, ASD children, no matter the MIA status, have specifically more difficulties in adaptive social behaviors with the others adaptive domains being less impacted [ 18 ]. Our results were consistent with the literature since one exploratory study reported more severe symptoms of social impairment - assessed with the SRS- in ASD-MIA + individuals [ 16 ]. One limitation is that we did not assess all the clinical variables that potentially influence socio-adaptive behaviour. Intelligence quotient, for example, was not integrated, whereas there were significant entanglements between IQ and adaptive functioning [ 19 ]. This limitation must be contrasted with a previous study finding MIA not to be associated with decreased cognitive functions [ 20 ]. Future studies should integrate all the dimensions of ASD children and frequent comorbidity, such as ID or ADHD, in order to decipher the socio-adaptive abnormalities in ASD children [ 21 ]. We also observed that MIA directly influenced the socio-adaptive behaviors of ASD individuals The effect of MIA appeared not mediated by the increase in the severity of autistic symptoms. This hypothesis mirrored findings in children with neurodevelopmental disorders (excluding ASD), in whom a history of AIM was associated, in a dose-response effect, with more externalizing and internalizing problems [ 22 ]. In mice, MIA directly triggers autistic-like symptoms through an effect on neuronal cytokine receptors in the cerebral cortex [ 3 ]. However, MIA also induced epigenetic changes of major transcriptional factors in the offspring that are independent of the onset of ASD core symptoms [ 23 ]. This effect is mediated by the maternal microbiota and leads to a long-term immune imbalance in the offspring, characterised by a peripheral increase in the Th17 lymphocyte subtype (Th17) [ 24 ]. Th17 are major pro-inflammatory lymphocytes and are in a constant and dynamic equilibrium with its anti-inflammatory counterpart regulatory T lymphocytes (Tregs) [ 25 , 26 ]. Interestingly, ASDindividuals displayed a peripheral increase in Th17 and a decrease in Tregs, which was more pronounced in those with a history of MIA [ 27 ]. Interestingly, a recent study on mice demonstrate that specific stimulation of Tregs in ASD pups from MIA mothers reverse autistic-like symptoms [ 28 ]. Overall, this suggests that the epigenetically mediated peripheral immune imbalance induced by MIA may participate in the socio-maladaptive behaviors in ASD and could be targeted by specific immunomodulatory strategies. Limitations One of the main limitation of our study was intrinsic to its retrospective design, which leads to a possible recall bias regarding the MIA event during pregnancy. To overcome this problem, we used a strict definition of MIA, but this will not replace a prospective study to confirm our results. Even if we pooled two cohorts, the population remains relatively small and to better decipher the influence of MIA, many clinical and biological factors need to be studied on larger cohorts to obtain the necessary statistical power. Nevertheless, all our results were validated by different and complementary statistical approaches with good model performance highlighting the robustness of our data. Finally, one additional limitation of our study was the limited number of covariables which potentially impacted socio-adaptive behaviors, that we included in the analysis. Intelligence quotient, for example, was not integrated, whereas there were significant entanglements between IQ and adaptive functioning [ 19 ]. Future studies should integrate additional dimensions related to ASD, such as intellectual developmental disorder or Attention Deficit / Hyperactive Disorder, to further decipher the impact of MIA on socio-adaptive impairment in ASD [ 21 ]. Conclusions MIA may affect at long term the socio-adaptive behavioral trajectories of individuals with ASD. Specific pathophysiological pathways may explain these clinical peculiarities of ASD- MIA + individuals, and may open the way to new perspectives in deciphering the phenotypic complexity of autism and the development of targeted immunotherapy strategies. Abbreviations ADOS: Autism Diagnostic Observation Schedule 2 nd edition ASD: autism spectrum disorders MIA: maternal immune activation SRS: Social Responsiveness Scale 2nd edition VABS: Vineland Adaptive Behavior Scales 2 nd edition Declarations Ethics approval : As part of the PARIS study, this study was approved by the local ethics committee of Robert Debré Hospital (2021-27 N° IDRCB: 2021-A00489-32). Informed consents were obtained before enrollment in the study. Availability of data and materials: The PARIS dataset and the code used during the current study are available from the corresponding author upon request. Due to ethical and legal restrictions, data involving clinical participants of the FACE-ASD cohort cannot be made publicly available. All relevant data are available upon request to the Fondation FondaMental for researchers who meet the criteria for access to confidential data. Competing interests: The authors declare that they have no competing interests Funding: This work was supported (in part) by the Fondation FondaMental, Créteil, France and by the Investissements d'Avenir programs managed by the ANR under references ANR-11-IDEX-0004-02 and ANR-10-COHO-10-01. Autors’ contribution: PE and AM contributed to data collection. PE, HP and NT analysed and interpreted the data. PE wrote the first version of the article and revised it after its revisions by co-authors. VV, EH, AAm, AAn, PA, JMB, SB, OB, MB, AC, NC, RC, DDF, CD, MG, FGB, FG, AK, ML, AL, FL, CL, EM, NR, CMS, MS, EZ, participated in the inclusion of children and in the revision of the article and approved its final version, and all agreed to be accountable for all aspects of the work. MR, DK and RD supervised this conception of this study References Lord C, Brugha TS, Charman T, Cusack J, Dumas G, Frazier T, et al. Autism spectrum disorder. Nat Rev Dis Primers. 2020;6:5. 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Ellul P, Rosenzwajg M, Peyre H, Fourcade G, Mariotti-Ferrandiz E, Trebossen V, et al. Regulatory T lymphocytes/Th17 lymphocytes imbalance in autism spectrum disorders: evidence from a meta-analysis. Mol Autism. 2021;12:68. Xu Z, Zhang X, Chang H, Kong Y, Ni Y, Liu R, et al. Rescue of maternal immune activation-induced behavioral abnormalities in adult mouse offspring by pathogen-activated maternal Treg cells. Nat Neurosci. 2021;24:818–30. Additional Declarations No competing interests reported. Supplementary Files 230213Figure1.pptx SupplFigure2.pptx SupplFigure3.pptx SupplFigure4.pptx Supplementarymaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Bouvard","email":"","orcid":"","institution":"Centre Hospitalier Charles-Perrens, Pôle Universitaire de Psychiatrie de L'enfant Et de L'adolescent","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Manuel","middleName":"","lastName":"Bouvard","suffix":""},{"id":181331312,"identity":"4714e31e-7eb8-4eca-aa04-bfae74e01319","order_by":11,"name":"Ariane Cartigny","email":"","orcid":"","institution":"University of Paris Cité","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ariane","middleName":"","lastName":"Cartigny","suffix":""},{"id":181331313,"identity":"0e9be8e3-7235-47a6-a427-bca6d867ef6e","order_by":12,"name":"Nathalie Coulon","email":"","orcid":"","institution":"Fondation FondaMental","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nathalie","middleName":"","lastName":"Coulon","suffix":""},{"id":181331314,"identity":"9c73a5b7-f161-4a69-833c-7cf0ba491bf7","order_by":13,"name":"Romain Coutelle","email":"","orcid":"","institution":"Centre Expert TSA-SDI, Université de Strasbourg, Centre Hospitalier de Versailles. UMR1018, Université Paris Saclay, Pasteur Insitute Paris","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Romain","middleName":"","lastName":"Coutelle","suffix":""},{"id":181331315,"identity":"be56b359-3839-4bce-9464-c98a6ede73cf","order_by":14,"name":"David Da Fonseca","email":"","orcid":"","institution":"Salvator University Hospital, Public Assistance-Marseille Hospitals, Aix- Marseille University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"David","middleName":"Da","lastName":"Fonseca","suffix":""},{"id":181331316,"identity":"82ff32f1-170f-40ae-bfe8-72e3aa5aa995","order_by":15,"name":"Caroline Demily","email":"","orcid":"","institution":"Fondation FondaMental","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Caroline","middleName":"","lastName":"Demily","suffix":""},{"id":181331317,"identity":"0d9453bc-ecee-48c9-8f03-d2cba90276f4","order_by":16,"name":"Marion Givaudan","email":"","orcid":"","institution":"Salvator University Hospital, Public Assistance-Marseille Hospitals, Aix- Marseille University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marion","middleName":"","lastName":"Givaudan","suffix":""},{"id":181331318,"identity":"c0604765-aa37-47a6-b3fe-fab5180c0e09","order_by":17,"name":"Fanny Gollier-Briant","email":"","orcid":"","institution":"CHU \u0026 Universite de Nantes","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fanny","middleName":"","lastName":"Gollier-Briant","suffix":""},{"id":181331319,"identity":"1f638745-867b-4f2e-b4db-1496cbaa064d","order_by":18,"name":"Fabian Guénolé","email":"","orcid":"","institution":"CHU de Caen, Caen Normandy University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fabian","middleName":"","lastName":"Guénolé","suffix":""},{"id":181331320,"identity":"a4edded2-31fd-407c-b92c-44dafe1c842e","order_by":19,"name":"Andrea Koch","email":"","orcid":"","institution":"University of Paris Cité","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Andrea","middleName":"","lastName":"Koch","suffix":""},{"id":181331321,"identity":"a679d4e3-ddc1-4d71-97b5-e65df5f9ae38","order_by":20,"name":"Marion Leboyer","email":"","orcid":"","institution":"Univ Paris Est Créteil, INSERM, IMRB, AP-HP, FHU ADAPT","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marion","middleName":"","lastName":"Leboyer","suffix":""},{"id":181331322,"identity":"024436e3-0886-4dff-acb1-e1659bb64bd7","order_by":21,"name":"Aline Lefebvre","email":"","orcid":"","institution":"University of Paris Cité","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Aline","middleName":"","lastName":"Lefebvre","suffix":""},{"id":181331323,"identity":"5a2a7ff7-e046-4b30-ba8a-7cf350a9752b","order_by":22,"name":"Florian Lejuste","email":"","orcid":"","institution":"Univ Paris Est Créteil, INSERM, IMRB, AP-HP, FHU ADAPT","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Florian","middleName":"","lastName":"Lejuste","suffix":""},{"id":181331324,"identity":"1a998dcb-3dda-45c7-8334-327f37731f01","order_by":23,"name":"Charlotte Levy","email":"","orcid":"","institution":"Centre Hospitalier Charles-Perrens, Pôle Universitaire de Psychiatrie de L'enfant Et de L'adolescent","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Charlotte","middleName":"","lastName":"Levy","suffix":""},{"id":181331325,"identity":"d96788f6-e424-4fbf-beba-a61feefb1dca","order_by":24,"name":"Eugénie Mendes","email":"","orcid":"","institution":"University of Paris Cité","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Eugénie","middleName":"","lastName":"Mendes","suffix":""},{"id":181331326,"identity":"69bc40a7-a760-49cc-8bd5-9f91ed531d80","order_by":25,"name":"Natalia Robert","email":"","orcid":"","institution":"Fondation FondaMental","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Natalia","middleName":"","lastName":"Robert","suffix":""},{"id":181331327,"identity":"91eb8fea-0264-40a1-b3ac-279c394b5499","order_by":26,"name":"Carmen M Schroder","email":"","orcid":"","institution":"Centre Expert TSA-SDI, Université de Strasbourg, Centre Hospitalier de Versailles. UMR1018, Université Paris Saclay, Pasteur Insitute Paris","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Carmen","middleName":"M","lastName":"Schroder","suffix":""},{"id":181331328,"identity":"8388cd88-3fff-43b7-adfb-aacc5cc2512c","order_by":27,"name":"Mario Speranza","email":"","orcid":"","institution":"Fondation FondaMental","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mario","middleName":"","lastName":"Speranza","suffix":""},{"id":181331329,"identity":"b8bea755-64bb-427d-a204-b3a9fab54971","order_by":28,"name":"Elodie Zante","email":"","orcid":"","institution":"Fondation FondaMental","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Elodie","middleName":"","lastName":"Zante","suffix":""},{"id":181331330,"identity":"8a2c38d0-6564-426f-8ecf-72f45976674a","order_by":29,"name":"Hugo Peyre","email":"","orcid":"","institution":"University of Paris 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23:58:41","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":21817,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-2623908/v1/afd374c57f1912cb9ff9fb5b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Maternal immune activation during pregnancy is associated with worst socio-adaptive behaviors in autism spectrum disorders","fulltext":[{"header":"Background","content":"\u003cp\u003eAutism spectrum disorders (ASD) are heterogeneous childhood-onset neurodevelopmental disorders characterised by social communication impairment or interaction and repetitive or stereotyped behaviours. Its incidence is 1 in 50 to 1 in 100 birth, affecting 52\u0026nbsp;million people worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The etiopathogenesis of ASD results from the close intertwining of genetic predispositions and environmental risk factors. Among the known environmental insults, maternal immune activation during the mid-pregnancy (MIA) - either due to maternal autoimmune diseases or to infections - is associated with an increased risk of ASD in the offspring [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In accordance with epidemiological evidences, well replicated pre clinical studies show that this association is mediated by a direct action of maternal immune mediators (\u003cem\u003ei.e.\u003c/em\u003e cytokines) on fetal cortical neurons, disrupting normal neurodevelopment and leading to autism-like behaviours in the pups [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Years of intensive research have made it possible to divide the common and heterogeneous autism spectrum into rarer but etiopathogenically homogeneous entities, based mainly on common genetic variants [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This approach allows to identify and better understand common pathophysiological pathways and thus the emergence of potential targeted therapies. Nonetheless, few studies have attempted to characterise ASD subgroup according to common pathogenic environmental factors. Despite a history of MIA being frequent, approximatively reported in 15% of ASD individuals, there is surprisingly little data on their specific clinical profiles.\u003c/p\u003e \u003cp\u003eClinical studies often use symptom scales to assess the clinical characteristics of individuals and the severity of the disorder, which do not reflect their adaptability to the environment. According to the \u003cem\u003eAmerican Association on Intellectual and Developmental Disorders\u003c/em\u003e (AAIDD), adaptive behaviour is \u0026laquo;the collection of conceptual, social, and practical skills that all people learn in order to function in their daily lives\u0026raquo; [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Adaptive skills thus represent a higher concept of functionning, taking into account all dimensions of a person in his/her environment [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The level of autonomy and adaptation of children with neurodevelopmental disorders is frequently assessed with the second edition of the Vineland Adaptive Behavior Scale (VABS) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] which measures adaptive behaviors from three main areas: communication, daily living skills and socialization.. As an exploratory study, we decided to use the VABS to explore the impact of MIA on the phenotype of individuals with ASD.\u003c/p\u003e \u003cp\u003eWe hypothesised that MIA\u003csup\u003e+\u003c/sup\u003e individuals would display more severe socio-maladaptive behaviors than MIA\u003csup\u003e\u0026minus;\u003c/sup\u003e ASD. To perform this study, we considered two independent cohorts of individuals with ASD (PARIS study and FACE ASD) screened for pregnancy history, and used a supervised and unsupervised statistical algorithms to decipher the interactions between MIA and adaptive behaviors in autism.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eWe included in our study children with ASD enrolled in the PARIS study, conducted by the Excellence Centre for Autism \u0026amp; Neuro-developmental Disorders (InovAND - Robert Debr\u0026eacute; Hospital, Paris, France) between March 2017 to April 2021. This study was approved by the local ethics committee (2021-27 N\u0026deg; IDRCB: 2021-A00489-32). We also enrolled ASD individuals from an independent sample from eight Expert Centers for ASD (Cr\u0026eacute;teil, Bordeaux, Grenoble, Versailles, Marseille, Caen, Strasbourg, Lyon) coordinated by Fondation FondaMental. The relevant Ethical Review Board (CPP- Est IV) approved the appraisal protocol on 18 June 2019. All participants gave their informed consent.\u003c/p\u003e \u003cp\u003eConsidering the frequency of the MIA event (12\u0026ndash;15%) and the number of individual per sample, we pooled all individuals to increase the power analysis of the study.\u003c/p\u003e \u003cp\u003eThe diagnosis of ASD was performed according to DSM-5 criteria [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] by summing up the information from the Autism Diagnostic Interview-Revised [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], the Autism Diagnostic Observation Schedule \u0026minus;\u0026thinsp;2nd edition (ADOS-2) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and clinical records of individuals. All participants were screened with a parental semi-structured interview for pre- and peri- natal history. We focused on any history of MIA during pregnancy. Based on this information, children were then split either into MIA (MIA\u003csup\u003e+\u003c/sup\u003e) or in non-MIA (MIA\u003csup\u003e-\u003c/sup\u003e) sub-groups. We considered mothers with a significant history of an MIA-related event when they were: (i) with an autoimmune disease as listed by the American Autoimmune Related Diseases Association [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and (ii) with a viral or bacterial infection during pregnancy with a fever over 38.5\u0026deg;C for more than 24 hours. Mothers with an infection resulting from a pathogen with a well-documented direct brain cytopathic effect (such as cytomegalovirus infection) were excluded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eBefore each analysis, the normality of the distribution of the variables was tested with a Shapiro-Wilk test. For continuous variables Student\u0026rsquo;s t-tests or Wilcoxon tests were used accordingly. For categorical variables, the Fisher test was used. Only linear models with a normal distribution of residuals were used. In order to test the predictions, we performed a hierarchical regression analysis. Hierarchical regression is a type of regression model in which predictors are added to or removed from the regression model in steps and/or blocks of variables. It allows for the analysis of the variance explained in a dependent variable by more than one predictor variable. Hierarchical regression analysis are in \u003cb\u003esupplementary materials\u003c/b\u003e. The final models of multivariate analysis (also found in supplementary materials) were all adjusted on sex and ASD scales (SRS T-score / ADOS total score). Unsupervised classification trees were generated using R package \u0026ldquo;Party\u0026rdquo; [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The relevance of the groups identified by the classification trees were then tested using ANOVA with post-hoc Tukey for multiple comparisons of means. Then, we performed supervised classification methods using the R package \u0026ldquo;mlr3''.[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] In sum, we split the sample in 2 groups, 80% of the individuals for training and the remaining for validation. As the MIA\u003csup\u003e+\u003c/sup\u003e individuals were under-represented, we used an oversampling method with a 3.5 ratio. The sample characteristics before and after oversampling are in Supplementary Fig.\u0026nbsp;1. For classification, we used both a logistic regression classification learner and a linear discriminant analysis classification learner. The learning parameters used by the model were then evaluated using the package R package \u0026laquo;iml\u0026raquo; [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] with three components: feature effects, Shapley values and feature importance. Lastly, to better understand the direct and indirect effects within this model, we used path analysis with R package \u0026laquo;lavaan\u0026raquo; [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Statistical analysis was performed using R studio version 4.2.1.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003eGeneral characteristics\u003c/h2\u003e\n \u003cp\u003eWe finally considered 295 mother-child dyads in our study, with a history of MIA reported in 14% of mothers (n\u0026thinsp;=\u0026thinsp;40) (MIA\u003csup\u003e+\u003c/sup\u003e). Dyads without a history of MIA (n\u0026thinsp;=\u0026thinsp;255, 86%) were used as a comparison group (MIA\u003csup\u003e\u0026minus;\u003c/sup\u003e).\u003c/p\u003e\n \u003cp\u003eThe prenatal history and birth parameters are provided in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMIA \u0026ndash;\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;255 (86%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMIA +\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;40 (14%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrenatal and birth parameters of the population studies.\u003c/strong\u003e MIA: Maternal immune activation\u0026nbsp;\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\u003c/tbody\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrenatal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes / No (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFisher test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eThreatened preterm delivery (TPD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15/240 (6/94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4/39 (10/90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh blood pressure (HBP)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8/247 (3/97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/38 (5/95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlacenta Praevia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/253 (0,8/98,2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/38 (5/95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePremature rupture of membranes (PROM)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0/255 (0/255)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3/37 (7,5/92,5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaterno-foetal infection (MFI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/253 (0,8/98,2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3/37 (7,5/92,5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex ratio M/F\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e211/43 (83/17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35/4 (90/10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBirth parameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWilcox test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight(cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50 (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight (g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3370 (1015)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3420 (545)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHead Circumference (cm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (1,5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAPGAR 1 minute\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAPGAR 5 minutes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eWe observed that mothers with MIA during pregnancy had more history of premature rupture of membranes (PROM) (p-value\u0026thinsp;=\u0026thinsp;0.002) and maternofetal infection (MFI) (p-value\u0026thinsp;=\u0026thinsp;0.02) than those without MIA. ASD-MIA\u003csup\u003e+\u003c/sup\u003e individuals did not differ from those without a history of MIA in term of symptoms severity estimated with the SRS T-score (p-value\u0026thinsp;=\u0026thinsp;0.6) or ADOS total score (p-value\u0026thinsp;=\u0026thinsp;0.4). Univariate analysis did not reveal any difference in any of the three sub-domain of the VABS: communication (p-value\u0026thinsp;=\u0026thinsp;0.3), ssocialisation (p-value\u0026thinsp;=\u0026thinsp;0.2), daily living skills (DLS) (p-value\u0026thinsp;=\u0026thinsp;0.4) domains (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMIA \u0026ndash;\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;255 (86%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMIA +\u003c/p\u003e\n \u003cp\u003eN\u0026thinsp;=\u0026thinsp;40 (14%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003eAutistic severity profile of the population studies.\u003c/strong\u003e MIA: Maternal immune activation, SRS: Social Responsiveness Scale 2nd edition; ADOS Autism Diagnostic Observation Schedule 2nd edition; VABS: Vineland adaptative behavior scale second edition\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\u003c/tbody\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWilcox test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSRS (T-score)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76 (16,5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eADOS (total score)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVABS \u0026ndash; Communication subdomain score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67 (36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64 (38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVABS - Socialisation subdomain score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64 (35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57 (36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eVABS - Daily Living Skills subdomain score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003eMore severe impact on adaptative behaviors related to socialization is associated with MIA during pregnancy\u003c/h2\u003e\n \u003cp\u003ePrevious studies found a more severe social impairement in MIA\u003csup\u003e+\u003c/sup\u003e children [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e]. We found, that SRS T-score and ADOS total score were correlated with the three sub-scores of VABS (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA). Accordingly, in adjusted analysis, we observed that more severe socio-maladaptive behaviors in ASD individuals was associated with a MIA during pregnancy (p-value\u0026thinsp;=\u0026thinsp;0.006) (Details of the hierarchical regression analysis are in \u003cstrong\u003esupplementary Table\u0026nbsp;1 and\u003c/strong\u003e Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). To confirm this association, we used a non-supervised classification tree isolating three groups of individuals (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB): (i) A MIA low-probability group (VABS - Socialisation\u0026thinsp;\u0026gt;\u0026thinsp;55 and ADOS total score\u0026thinsp;\u0026gt;\u0026thinsp;15) with 1% of MIA\u003csup\u003e+\u003c/sup\u003e; (ii) a medium-probability group (VABS - Socialisation\u0026thinsp;\u0026gt;\u0026thinsp;55 and ADOS total score\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;15) with 11% of MIA\u003csup\u003e+\u003c/sup\u003e; and (iii) a high-probability group (VABS - Socialisation\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;55) with 17% of MIA\u003csup\u003e+\u003c/sup\u003e. Significant differences between the high-probability group and the low-probability group were observed (p-value\u0026thinsp;=\u0026thinsp;0.002).\u003c/p\u003e\n \u003cp\u003eFinally, we further validated our results by applying a supervised classification algorithm with two distinct predictive models. Applying logistic regression classification, we discriminated MIA\u003csup\u003e+\u003c/sup\u003e individuals with an accuracy of 70%, a sensitivity of 84%, a specificity of 27% and an area under the curve (AUC) of 72%. In accordance with our initial hypothesis, the most robust parameter to classify children was the VABS - Socialisation score followed by ADOS total score (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC \u003cstrong\u003eand Supplementary Fig.\u0026nbsp;2A and 2B\u003c/strong\u003e). Linear discriminant analysis classification (LDA) reported similar results with an accuracy of 72%, a sensitivity of 84%, a specificity of 33% and AUC of 66%. Of note, the VABS - Socialisation score was also the most important parameter allowing classification, but in LDA, both ADOS total score and SRS T-score were pertinent to classify children (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eD). Considering the communication domain, we observed that more severe score was also associated with a history of MIA (p-value\u0026thinsp;=\u0026thinsp;0.045) (details of the multiple linear regression results in \u003cstrong\u003esupplementary Table\u0026nbsp;3\u003c/strong\u003e). We next used a non-supervised classification tree also isolating three groups of individuals (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eE): (i) A MIA low-probability group (VABS - communication\u0026thinsp;\u0026gt;\u0026thinsp;66) with 10% of MIA\u003csup\u003e+\u003c/sup\u003e ; (ii) a medium-probability group (VABS \u0026ndash; Communication\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;66 and ADOS total score\u0026thinsp;\u0026gt;\u0026thinsp;19 ) with 12% of MIA\u003csup\u003e+\u003c/sup\u003e ; and (iii) a high-probability group (VABS - Communication\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;66 and ADOS total score\u0026thinsp;\u0026lt;\u0026thinsp;19)) with 18% of MIA\u003csup\u003e+\u003c/sup\u003e. No significant differences was found between groups (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.08). Thus, we considered that the communication domain of the VABS was not associated with MIA. Lastly, no association was observed between DLS and MIA (p-value\u0026thinsp;=\u0026thinsp;0.2) (\u003cstrong\u003esupplementary Table\u0026nbsp;4\u003c/strong\u003e).\u003c/p\u003e\n \u003cp\u003eIn sum, we found that, in ASD children, more severe adaptive behaviours in socialisation were associated with a higher probability of a history of MIA during pregnancy.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003eMIA may directly affected the socio-maladaptive behaviors in autism\u003c/h2\u003e\n \u003cp\u003eWe observed that MIA was associated with more pregnancy complications also known to increase independently the risk for ASD (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e]. Pregnancy complications and more severe ASD symptomatology were correlated with more adaptive behaviours later on (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;3\u003c/strong\u003e). Adjusting for these potential factors and corroborating our previous results, we investigated whether a history of MIA was associated with poorer adaptive behavior and if so, the mediator of this association.\u003c/p\u003e\n \u003cp\u003eUsing adjustment models, we found no any association between the history of MIA and communication (p-value\u0026thinsp;=\u0026thinsp;0.15) or DLS (p-value\u0026thinsp;=\u0026thinsp;0.63) sub-domain but a significant association with poorer socio-adaptive behaviours (p-value\u0026thinsp;=\u0026thinsp;0.03) (\u003cstrong\u003esupplementary Tables\u0026nbsp;5, 6 and 7\u003c/strong\u003e). Unsupervised analysis with a linear model regression learner confirmed this association (mean absolute error\u0026thinsp;=\u0026thinsp;20.2; mean qquare error\u0026thinsp;=\u0026thinsp;562.7; root mean square error\u0026thinsp;=\u0026thinsp;23.7, R-square\u0026thinsp;=\u0026thinsp;0.16) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e\n \u003cp\u003eAccording to feature importance, MIA appeared to predict the intensity of communication deficit, just after the intensity of the global autistic symptom severity itself (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB and Supplementary Fig. 4). Finally, we explored whether there was a causal link between the MIA and the impairment intensity of socio-adaptive skills. We used structural equation modelling and applied a path analysis to our dataset. We found, with a good model performance (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC), that MIA influenced directly the socio-adaptive skills of children, independently of pregnancy complications or global severity of autism symptoms (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eUsing multiple and complementary statistical approaches, we found that ASD individuals with a history of MIA during pregnancy displayed poorer socio-adaptive skills. For individual with a VABS socialization subdomain score\u0026thinsp;\u0026lt;\u0026thinsp;55, almost 20% of children had a history of MIA, compared to 1\u0026ndash;10% for those with a VABS socialization subdomain score\u0026thinsp;\u0026gt;\u0026thinsp;55. Social-adaptive skills are a central node of autism symptomatology. Compared to healthy children, ASD children, no matter the MIA status, have specifically more difficulties in adaptive social behaviors with the others adaptive domains being less impacted [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Our results were consistent with the literature since one exploratory study reported more severe symptoms of social impairment - assessed with the SRS- in ASD-MIA\u003csup\u003e+\u003c/sup\u003e individuals [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. One limitation is that we did not assess all the clinical variables that potentially influence socio-adaptive behaviour. Intelligence quotient, for example, was not integrated, whereas there were significant entanglements between IQ and adaptive functioning [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This limitation must be contrasted with a previous study finding MIA not to be associated with decreased cognitive functions [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Future studies should integrate all the dimensions of ASD children and frequent comorbidity, such as ID or ADHD, in order to decipher the socio-adaptive abnormalities in ASD children [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe also observed that MIA directly influenced the socio-adaptive behaviors of ASD individuals The effect of MIA appeared not mediated by the increase in the severity of autistic symptoms. This hypothesis mirrored findings in children with neurodevelopmental disorders (excluding ASD), in whom a history of AIM was associated, in a dose-response effect, with more externalizing and internalizing problems [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In mice, MIA directly triggers autistic-like symptoms through an effect on neuronal cytokine receptors in the cerebral cortex [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, MIA also induced epigenetic changes of major transcriptional factors in the offspring that are independent of the onset of ASD core symptoms [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This effect is mediated by the maternal microbiota and leads to a long-term immune imbalance in the offspring, characterised by a peripheral increase in the Th17 lymphocyte subtype (Th17) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Th17 are major pro-inflammatory lymphocytes and are in a constant and dynamic equilibrium with its anti-inflammatory counterpart regulatory T lymphocytes (Tregs) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Interestingly, ASDindividuals displayed a peripheral increase in Th17 and a decrease in Tregs, which was more pronounced in those with a history of MIA [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Interestingly, a recent study on mice demonstrate that specific stimulation of Tregs in ASD pups from MIA mothers reverse autistic-like symptoms [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Overall, this suggests that the epigenetically mediated peripheral immune imbalance induced by MIA may participate in the socio-maladaptive behaviors in ASD and could be targeted by specific immunomodulatory strategies.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eOne of the main limitation of our study was intrinsic to its retrospective design, which leads to a possible recall bias regarding the MIA event during pregnancy. To overcome this problem, we used a strict definition of MIA, but this will not replace a prospective study to confirm our results. Even if we pooled two cohorts, the population remains relatively small and to better decipher the influence of MIA, many clinical and biological factors need to be studied on larger cohorts to obtain the necessary statistical power. Nevertheless, all our results were validated by different and complementary statistical approaches with good model performance highlighting the robustness of our data.\u003c/p\u003e \u003cp\u003eFinally, one additional limitation of our study was the limited number of covariables which potentially impacted socio-adaptive behaviors, that we included in the analysis. Intelligence quotient, for example, was not integrated, whereas there were significant entanglements between IQ and adaptive functioning [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Future studies should integrate additional dimensions related to ASD, such as intellectual developmental disorder or Attention Deficit / Hyperactive Disorder, to further decipher the impact of MIA on socio-adaptive impairment in ASD [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eMIA may affect at long term the socio-adaptive behavioral trajectories of individuals with ASD. Specific pathophysiological pathways may explain these clinical peculiarities of ASD- MIA\u003csup\u003e+\u003c/sup\u003e individuals, and may open the way to new perspectives in deciphering the phenotypic complexity of autism and the development of targeted immunotherapy strategies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eADOS: Autism Diagnostic Observation Schedule 2\u003csup\u003end\u003c/sup\u003e edition\u003c/p\u003e\n\u003cp\u003eASD: autism spectrum disorders\u003c/p\u003e\n\u003cp\u003eMIA: maternal immune activation\u003c/p\u003e\n\u003cp\u003eSRS: Social Responsiveness Scale 2nd edition\u003c/p\u003e\n\u003cp\u003eVABS: Vineland Adaptive Behavior Scales 2\u003csup\u003end\u003c/sup\u003e edition\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval : As part of the PARIS study, this study was approved by the local ethics committee of Robert Debr\u0026eacute; Hospital (2021-27 N\u0026deg; IDRCB: 2021-A00489-32). Informed consents were obtained before enrollment in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eAvailability of data and materials: The PARIS dataset and the code used during the current study are available from the corresponding author upon request. Due to ethical and legal restrictions, data involving clinical participants of the FACE-ASD cohort cannot be made publicly available. All relevant data are available upon request to the Fondation FondaMental for researchers who meet the criteria for access to confidential data.\u003c/p\u003e\n\u003cp\u003eCompeting interests:\u0026nbsp;The authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003eFunding: This work was supported (in part) by the Fondation FondaMental, Cr\u0026eacute;teil, France and by the Investissements d\u0026apos;Avenir programs managed by the ANR under references ANR-11-IDEX-0004-02 and ANR-10-COHO-10-01.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Autors\u0026rsquo; contribution: PE and AM contributed to data collection. PE, HP and NT analysed and interpreted the data. PE wrote the first version of the article and revised it after its revisions by co-authors. VV, EH, AAm, AAn, PA, JMB, SB, OB, MB, AC, NC, RC, DDF, CD, MG, FGB, FG, AK, ML, AL, FL, CL, EM, NR, CMS, MS, EZ, participated in the inclusion of children and in the revision of the article and approved its final version, and all agreed to be accountable for all aspects of the work. MR, DK and RD supervised this conception of this study\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLord C, Brugha TS, Charman T, Cusack J, Dumas G, Frazier T, et al. Autism spectrum disorder. Nat Rev Dis Primers. 2020;6:5. \u003c/li\u003e\n\u003cli\u003eHan VX, Patel S, Jones HF, Dale RC. Maternal immune activation and neuroinflammation in human neurodevelopmental disorders. Nat Rev Neurol. 2021;17:564\u0026ndash;79. \u003c/li\u003e\n\u003cli\u003eChoi GB, Yim YS, Wong H, Kim S, Kim H, Kim SV, et al. The maternal interleukin-17a pathway in mice promotes autism-like phenotypes in offspring. Science. 2016;351:933\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eBourgeron T. From the genetic architecture to synaptic plasticity in autism spectrum disorder. Nat Rev Neurosci. 2015;16:551\u0026ndash;63. \u003c/li\u003e\n\u003cli\u003eAdaptive Behavior [Internet]. AAIDD_CMS. [cited 2022 Dec 15]. Available from: https://www.aaidd.org/intellectual-disability/definition/adaptive-behavior\u003c/li\u003e\n\u003cli\u003eTillmann J, San Jos\u0026eacute; C\u0026aacute;ceres A, Chatham CH, Crawley D, Holt R, Oakley B, et al. Investigating the factors underlying adaptive functioning in autism in the EU-AIMS Longitudinal European Autism Project. Autism Res. 2019;12:645\u0026ndash;57. \u003c/li\u003e\n\u003cli\u003eKanne SM, Gerber AJ, Quirmbach LM, Sparrow SS, Cicchetti DV, Saulnier CA. The role of adaptive behavior in autism spectrum disorders: implications for functional outcome. J Autism Dev Disord. 2011;41:1007\u0026ndash;18. \u003c/li\u003e\n\u003cli\u003eDiagnostic and statistical manual of mental disorders: DSM-5. 5th ed. Washington: American psychiatric association; 2013. \u003c/li\u003e\n\u003cli\u003eLord C, Rutter M, Le Couteur A. Autism Diagnostic Interview-Revised: A revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Dev Disord. 1994;24:659\u0026ndash;85. \u003c/li\u003e\n\u003cli\u003eLord C, Risi S, Lambrecht L, Cook, Jr. EH, Leventhal BL, DiLavore PC, et al. [No title found]. Journal of Autism and Developmental Disorders. 2000;30:205\u0026ndash;23. \u003c/li\u003e\n\u003cli\u003eAutoimmune Disease List \u0026bull; AARDA [Internet]. AARDA. 2016 [cited 2021 Feb 19]. Available from: https://www.aarda.org/diseaselist/\u003c/li\u003e\n\u003cli\u003eHothorn T, Seibold H, Zeileis A. partykit: A Toolkit for Recursive Partytioning [Internet]. 2021 [cited 2022 Jun 7]. Available from: https://CRAN.R-project.org/package=partykit\u003c/li\u003e\n\u003cli\u003eLang [cre M, aut, Bischl B, Richter J, Schratz P, Casalicchio G, et al. mlr3: Machine Learning in R - Next Generation [Internet]. 2022 [cited 2022 Dec 15]. Available from: https://CRAN.R-project.org/package=mlr3\u003c/li\u003e\n\u003cli\u003eMolnar C, Schratz P. iml: Interpretable Machine Learning [Internet]. 2022 [cited 2022 Dec 15]. Available from: https://CRAN.R-project.org/package=iml\u003c/li\u003e\n\u003cli\u003eRosseel Y, Jorgensen TD, Rockwood N, Oberski D, Byrnes J, Vanbrabant L, et al. lavaan: Latent Variable Analysis [Internet]. 2022 [cited 2022 Dec 15]. Available from: https://CRAN.R-project.org/package=lavaan\u003c/li\u003e\n\u003cli\u003ePatel S, Masi A, Dale RC, Whitehouse AJO, Pokorski I, Alvares GA, et al. Social impairments in autism spectrum disorder are related to maternal immune history profile. Mol Psychiatry. 2017; \u003c/li\u003e\n\u003cli\u003ePierrat V, Marchand-Martin L, Marret S, Arnaud C, Benhammou V, Cambonie G, et al. Neurodevelopmental outcomes at age 5 among children born preterm: EPIPAGE-2 cohort study. BMJ. 2021;373:n741. \u003c/li\u003e\n\u003cli\u003eKim SH, Bal VH, Lord C. Adaptive Social Abilities in Autism. In: Patel VB, Preedy VR, Martin CR, editors. Comprehensive Guide to Autism [Internet]. New York, NY: Springer New York; 2014 [cited 2022 Dec 15]. p. 1119\u0026ndash;32. Available from: http://link.springer.com/10.1007/978-1-4614-4788-7_61\u003c/li\u003e\n\u003cli\u003eTamm L, Day HA, Duncan A. Comparison of Adaptive Functioning Measures in Adolescents with Autism Spectrum Disorder Without Intellectual Disability. J Autism Dev Disord. 2022;52:1247\u0026ndash;56. \u003c/li\u003e\n\u003cli\u003ePatel S, Dale RC, Rose D, Heath B, Nordahl CW, Rogers S, et al. Maternal immune conditions are increased in males with autism spectrum disorders and are associated with behavioural and emotional but not cognitive co-morbidity. Transl Psychiatry. 2020;10:286. \u003c/li\u003e\n\u003cli\u003eNishimura T, Kato T, Okumura A, Harada T, Iwabuchi T, Rahman MS, et al. Trajectories of Adaptive Behaviors During Childhood in Females and Males in the General Population. Front Psychiatry. 2022;13:817383. \u003c/li\u003e\n\u003cli\u003ePatel S, Cooper MN, Jones H, Whitehouse AJO, Dale RC, Guastella AJ. Maternal immune-related conditions during pregnancy may be a risk factor for neuropsychiatric problems in offspring throughout childhood and adolescence. Psychol Med. 2021;51:2904\u0026ndash;14. \u003c/li\u003e\n\u003cli\u003eLim AI, McFadden T, Link VM, Han S-J, Karlsson R-M, Stacy A, et al. Prenatal maternal infection promotes tissue-specific immunity and inflammation in offspring. Science. 2021;373:eabf3002. \u003c/li\u003e\n\u003cli\u003eKim E, Paik D, Ramirez RN, Biggs DG, Park Y, Kwon H-K, et al. Maternal gut bacteria drive intestinal inflammation in offspring with neurodevelopmental disorders by altering the chromatin landscape of CD4+ T cells. Immunity. 2022;55:145-158.e7. \u003c/li\u003e\n\u003cli\u003eBettelli E, Oukka M, Kuchroo VK. T(H)-17 cells in the circle of immunity and autoimmunity. Nat Immunol. 2007;8:345\u0026ndash;50. \u003c/li\u003e\n\u003cli\u003eWeaver CT, Hatton RD. Interplay between the TH17 and TReg cell lineages: a (co-)evolutionary perspective. Nat Rev Immunol. 2009;9:883\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eEllul P, Rosenzwajg M, Peyre H, Fourcade G, Mariotti-Ferrandiz E, Trebossen V, et al. Regulatory T lymphocytes/Th17 lymphocytes imbalance in autism spectrum disorders: evidence from a meta-analysis. Mol Autism. 2021;12:68. \u003c/li\u003e\n\u003cli\u003eXu Z, Zhang X, Chang H, Kong Y, Ni Y, Liu R, et al. Rescue of maternal immune activation-induced behavioral abnormalities in adult mouse offspring by pathogen-activated maternal Treg cells. Nat Neurosci. 2021;24:818\u0026ndash;30. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Neuroimmunology, Autoimmune diseases, Inflammation, Machine Learning","lastPublishedDoi":"10.21203/rs.3.rs-2623908/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2623908/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAutism spectrum disorders (ASD) are neurodevelopmental disorders characterised by deficits in social communication or interaction and repetitive behaviours. Maternal immune activation (MIA) during the mid-pregnancy is a known risk factor for ASD. Although reported in 15% of affected individuals, little is known about the specificity of their clinical profiles. Adaptive skills represent a holistic approach to a person's competencies and reflect specifically in autism, their strengths and difficulties.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this study, we hypothesised that individual with ASD with a history of MIA (MIA\u003csup\u003e+\u003c/sup\u003e) could be more severely socio-adaptively impaired than those without MIA during pregnancy (MIA\u003csup\u003e\u0026minus;\u003c/sup\u003e). To answer this question, we considered two independent cohorts of individuals with ASD (PARIS study and FACE ASD) screened for pregnancy history, and used a supervised and unsupervised statistical approach.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe included 295 mother-child dyads with 14% of them with MIA\u003csup\u003e+\u003c/sup\u003e. We found that ASD-MIA\u003csup\u003e+\u003c/sup\u003e individuals displayed more severe maladaptive behaviors, specifically in their socialization abilities. MIA\u003csup\u003e+\u003c/sup\u003e directly influenced individual's socio-adaptive skills, independent of other covariates, including ASD severity. Interestingly, MIA\u003csup\u003e+\u003c/sup\u003e may affected persistently the socio-adaptive behavioral trajectories of individuals with ASD.\u003c/p\u003e\u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003e: The current study has a retrospective design with possible recall bias regarding the MIA event and, even if pooled from two cohorts, has a relatively small population. In addition, we were limited by the number of covariables available potentially impacted socio-adaptive behaviors. Larger prospective study with additional dimensions related to ASD is needed to confirm our results\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eSpecific pathophysiological pathways may explain these clinical peculiarities of ASD- MIA\u003csup\u003e+\u003c/sup\u003e individuals, and may open the way to new perspectives in deciphering the phenotypic complexity of autism and for the development of specific immunomodulatory strategies.\u003c/p\u003e","manuscriptTitle":"Maternal immune activation during pregnancy is associated with worst socio-adaptive behaviors in autism spectrum disorders","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-03-10 23:50:36","doi":"10.21203/rs.3.rs-2623908/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2422ff34-a567-436f-a5ba-1c7af7456d32","owner":[],"postedDate":"March 10th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-03-11T14:29:15+00:00","versionOfRecord":[],"versionCreatedAt":"2023-03-10 23:50:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2623908","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2623908","identity":"rs-2623908","version":["v1"]},"buildId":"GqpaHPwrfC8PjnIFayRh5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}